Warning: SOME ARGUMENT VALUES ARE DEPRECATED: (data_format='NCHW'). They will be removed in a future version.
Instructions for updating:
NCHW for data_format is deprecated, use NCW insteadWarning: SOME ARGUMENT VALUES ARE DEPRECATED: (data_format='NHWC'). They will be removed in a future version.
Instructions for updating:
NHWC for data_format is deprecated, use NWC instead

Given an input tensor of shape
[batch, in_width, in_channels]
if data_format is "NWC", or
[batch, in_channels, in_width]
if data_format is "NCW",
and a filter / kernel tensor of shape
[filter_width, in_channels, out_channels], this op reshapes
the arguments to pass them to conv2d to perform the equivalent
convolution operation.

Internally, this op reshapes the input tensors and invokes tf.nn.conv2d.
For example, if data_format does not start with "NC", a tensor of shape
[batch, in_width, in_channels]
is reshaped to
[batch, 1, in_width, in_channels],
and the filter is reshaped to
[1, filter_width, in_channels, out_channels].
The result is then reshaped back to
[batch, out_width, out_channels]
(where out_width is a function of the stride and padding as in conv2d) and
returned to the caller.

Args:

value: A 3D Tensor. Must be of type float16, float32, or float64.

filters: A 3D Tensor. Must have the same type as value.

stride: An integer. The number of entries by which
the filter is moved right at each step.

padding: 'SAME' or 'VALID'

use_cudnn_on_gpu: An optional bool. Defaults to True.

data_format: An optional string from "NWC", "NCW". Defaults
to "NWC", the data is stored in the order of
[batch, in_width, in_channels]. The "NCW" format stores
data as [batch, in_channels, in_width].